U.S. patent application number 16/558972 was filed with the patent office on 2020-04-16 for method to improve das channel location accuracy using global inversion.
This patent application is currently assigned to Halliburton Energy Services, Inc.. The applicant listed for this patent is Halliburton Energy Services, Inc.. Invention is credited to Andreas Ellmauthaler, Amit Padhi, Mark Elliott Willis, Xiang Wu.
Application Number | 20200116883 16/558972 |
Document ID | / |
Family ID | 70161791 |
Filed Date | 2020-04-16 |
United States Patent
Application |
20200116883 |
Kind Code |
A1 |
Padhi; Amit ; et
al. |
April 16, 2020 |
Method To Improve DAS Channel Location Accuracy Using Global
Inversion
Abstract
A method for identifying a location of a distributed acoustic
system channel in a distributed acoustic system. The method may
comprise generating a two or three dimensional layer model
interface with an information handling system, preparing a P-wave
first arrival pick time table, estimating an initial model layer
properties, estimating a location of the distributed acoustic
system channels, preparing an overburden file of layer properties,
running an anisotropic ray tracing, defining an upper and a lower
limits for model parameters, specifying parameters for the
inversion, running an inversion, selecting a solution based at
least in part on stored error predictions, and calculating a mean
and a standard deviation of an inverted model parameter.
Inventors: |
Padhi; Amit; (Houston,
TX) ; Willis; Mark Elliott; (Katy, TX) ; Wu;
Xiang; (Singapore, SG) ; Ellmauthaler; Andreas;
(Houston, TX) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Halliburton Energy Services, Inc. |
Houston |
TX |
US |
|
|
Assignee: |
Halliburton Energy Services,
Inc.
Houston
TX
|
Family ID: |
70161791 |
Appl. No.: |
16/558972 |
Filed: |
September 3, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
62746405 |
Oct 16, 2018 |
|
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|
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01V 1/42 20130101; G01V
2210/65 20130101; G01V 1/282 20130101; G01V 1/305 20130101; G01V
1/302 20130101; G01V 1/303 20130101; G01V 2210/64 20130101; G01V
1/288 20130101; G01V 1/226 20130101 |
International
Class: |
G01V 1/30 20060101
G01V001/30; G01V 1/28 20060101 G01V001/28 |
Claims
1. A method comprising: generating a multi-dimensional model
interface with an information handling system; preparing a time
table for a first arrival of a P-wave based at least in part on the
multi-dimensional model interface; estimating one or more initial
model layer properties based at least in part on the
multi-dimensional model interface; estimating a location of one or
more distributed acoustic system channels based at least in part on
the multi-dimensional model interface; creating a forward model
based at least in part on the location of the one or more
distributed acoustic system channels and the one or more initial
model layer properties; running an anisotropic ray tracing on the
forward model; defining an upper limit and a lower limit for model
parameters within the forward model; specifying parameters for an
inversion for the model parameters; running the inversion with the
model parameters to populate one or more members; selecting a
solution from the one or more members based at least in part on
stored error predictions; and calculating a mean and a standard
deviation of an inverted model parameter to determine the location
of the one or more distributed acoustic system channels.
2. The method of claim 1, wherein the multi-dimensional model
interface is a gridded velocity model.
3. The method of claim 1, further comprising storing an initial
choice of a ray parameter.
4. The method of claim 1, further comprising defining the upper
limit and the lower limit for a channel location search space.
5. The method of claim 1, wherein the inversion is a non-linear
inversion.
6. The method of claim 5, wherein the parameters for the inversion
are a number of generations, a crossover probability or a step
size.
7. The method of claim 1, further comprising collecting all
population members from the inversion.
8. The method of claim 1, wherein the generating the
multi-dimensional model interface is performed at least in part
with a seismic depth image.
9. The method of claim 1, wherein the multi-dimensional model
interface includes at least three P-wave anisotropy parameters per
layer.
10. The method of claim 1, further comprising disposing the one or
more distributed acoustic system channels into a wellbore.
11. A system comprising: a distributed acoustic system, wherein the
distributed acoustic system comprises: a fiber optic cable; and a
seismic source; and an information handling system configured to:
generate a three dimensional model interface; prepare a time table
for a first arrival of a P-wave based at least in part on a
multi-dimensional model interface; estimate one or more initial
model layer properties based at least in part on the
multi-dimensional model interface; estimate a location of one or
more distributed acoustic system channels based at least in part on
the multi-dimensional model interface; create a forward model based
at least in part on the location of the one or more distributed
acoustic system channels and the one or more initial model layer
properties; run an anisotropic ray tracing on the forward model;
define an upper limit and a lower limit for model parameters within
the forward model; specify parameters for an inversion for the
model parameter; run the inversion with the model parameters to
populate one or more members; select a solution from the one or
more members based at least in part on stored error predictions;
and calculate a mean and a standard deviation of an inverted model
parameter to determine the location of the one or more distributed
acoustic system channels.
12. The system of claim 11, wherein the multi-dimensional model
interface is a gridded velocity model.
13. The system of claim 11, wherein the information handling system
is configured to store an initial choice of a ray parameter.
14. The system of claim 11, wherein the information handling system
is configured to define the upper limit and the lower limit for a
channel location search space.
15. The system of claim 11, wherein the inversion is a non-linear
inversion.
16. The system of claim 15, wherein the parameters for the
inversion are a number of generations, a crossover probability, or
a step size.
17. A method comprising: defining a search window for a
multi-dimensional model interface to locate one or more distributed
acoustic system channels; generating a random population of
solutions for a location of the one or more distributed acoustic
system channels; determining an error for at least one member of
the population of solutions; adding at least one penalty to the
population of solutions; choosing a solution from the population of
solutions; determining a mutant solution for the population of
solutions; generating a trial solution based at least in part on
the mutant solution and the population of solutions; comparing the
trial solution to a target solution to create one or more child
solutions; and storing the one or more child solutions within an
information handling system.
18. The method of claim 17, wherein the one or more child solutions
are found from a greedy criterion.
19. The method of claim 17, further comprising applying a stopping
criterion to the one or more child solutions.
20. The method of claim 19, wherein the stopping criterion compare
the one or more child solutions to error predictions.
Description
BACKGROUND
[0001] Bore holes drilled into subterranean formations may enable
recovery of desirable fluids (e.g., hydrocarbons) using a number of
different techniques. Knowing the type of formation during drilling
operations may be beneficial to operators as a bottom hole assembly
traverses through different formations. For example, currently
after the conclusion of drilling operations, a wireline system,
distributed acoustic system (DAS), may be disposed within the
borehole and measurements may be taken, covering a specific depth
range. A vibration source, disposed on the surface, may be
activated to cast seismic waves into formations below. A fiberoptic
system may detect and allow the recording of the seismic waves as
they traverse and/or reflect through the formation. The processing
of the recording signals may be used to produce a profile of
seismic velocity for the rock formations traversed by the waves,
which may improve the identification of the rock formations or to
measure various rock properties. This process of measuring the
velocity of seismic waves may be repeated many times to form a
vertical seismic profile (VSP).
[0002] However, DAS technology suffers from a fundamental problem
arising out of positional uncertainty of the DAS channels. Some of
the reasons for such uncertainty are incorrect assumptions about
propagation velocity of the light pulse in the fiber, imprecise
knowledge of the nominal length of the surface fiber cable, and
fiber overstuffing. While it is possible to calibrate the depth of
DAS channels using geophone data collected prior to DAS survey or
using optical attenuation points, these methods have their
limitations. For example, a geophone dataset may simply not be
available in some cases. On the other hand, the use of optical
attenuation points to calibrate depths may also not be well suited
to several cases because of the lack of sufficient number of such
calibration points.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] These drawings illustrate certain aspects of some examples
of the present disclosure, and should not be used to limit or
define the disclosure.
[0004] FIG. 1 illustrates an example of a distributed acoustic
sensing system operating on a well system;
[0005] FIG. 2 illustrates a synthetic test on a model;
[0006] FIG. 3 is a graph illustrating inverted locations of a DAS
channel;
[0007] FIG. 4 is a flowchart for differential evolution;
[0008] FIG. 5 is a flow chart for an overall inversion algorithm
for estimating layer properties; and
[0009] FIGS. 6A-6D illustrate different examples of a fiber optic
cable deployed downhole in a distributed acoustic sensing
system.
DETAILED DESCRIPTION
[0010] This disclosure relates to use of distributed acoustic
sensing ("DAS") systems in a downhole environment. Examples may
provide systems and methods for a methodology to invert picked
travel times of the direct wave recorded on a DAS VSP data set to
simultaneously obtain the DAS channel locations and anisotropic
velocities of a three dimensional ("3D") layered model.
[0011] The DAS channel location inversion may be constrained by the
measured well trajectory (from the well deviation survey) and may
reduce uncertainties from the range of tens of meters to a few
meters around the true location.
[0012] FIG. 1 generally illustrates an example of a well system 100
that may be used in a wellbore 102, which may include DAS system
104. It should be noted that well system 100 may be one example of
a wide variety of well systems in which the principles of this
disclosure may be utilized. Accordingly, it should be understood
that the principles of this disclosure may not be limited to any of
the details of the depicted well system 100, or the various
components thereof, depicted in the drawings or otherwise described
herein. For example, it is not necessary in keeping with the
principles of this disclosure for completed well system 100 to
include a generally vertical wellbore section and/or a generally
horizontal wellbore section. Moreover, it is not necessary for
formation fluids to be only produced from formation 118 since, in
other examples, fluids may be injected into subterranean formation
118, or fluids may be both injected into and produced from
subterranean formation 118, without departing from the scope of the
disclosure. Additionally, wellbore 102 may be a producing well, an
injection well, a recovery well, and/or an uncompleted well.
Further, while FIG. 1 generally depicts land-based system, those
skilled in the art will readily recognize that the principles
described herein are equally applicable to a subsea operation,
without departing from the scope of the disclosure.
[0013] In FIG. 1, DAS system 104 may be disposed along production
tubing 108 and further within casing 110. As disclosed below, DAS
system 104 may be permanently installed, semi-permanently
installed, or temporally deployed in a wireline system, slickline
system, coiled tubing system, and/or the like. DAS system 104 may
include a fiber optic cable 106. Fiber optic cable 106 may be
single mode, multi-mode, or a plurality thereof. In examples, fiber
optic cable 106 may be permanently installed and/or temporarily
installed in wellbore 102. Without limitation, DAS system 104 may
operate and function to measure and produce a time-lapse vertical
seismic profile ("VSP"). Light may be launched into the fiber optic
cable 106 from surface 122 with light returned via the same fiber
optic cable 106 detected at the surface 122. DAS system 104 may
detect acoustic energy along the fiber optic cable 106 from the
detected light returned to the surface 122. For example,
measurement of backscattered light (e.g., Rayleigh backscattering)
can be used to detect the acoustic energy (e.g., seismic waves 114
or reflected seismic waves 116). In additional examples, Bragg
Grating or other suitable device can be used with the fiber optic
cable 106 for detection of acoustic energy along the fiber optic
cable. While FIG. 1 describes DAS system 104 and use of fiber optic
cable 106 as the subsurface sensory array for detection of acoustic
energy, it should be understood that examples may include other
techniques for detection of acoustic energy in the wellbore 102. In
examples, fiber optic cable 106 may be clamped to production tubing
108. However, fiber optic cable 106 may be clamped to production
tubing through connection device 112 by any suitable means. It
should be noted that fiber optic cable 106 may also be cemented in
place within casing 110 and/or attached to casing 110 by any
suitable means. Additionally, fiber optic cable 106 may be attached
to coil tubing and/or a conveyance. A conveyance may include any
suitable means for providing mechanical conveyance for fiber optic
cable 106, including, but not limited to, wireline, slickline,
pipe, drill pipe, downhole tractor, or the like. In some
embodiments, the conveyance may provide mechanical suspension, as
well as electrical connectivity, for fiber optic cable 106. The
conveyance may comprise, in some instances, a plurality of
electrical conductors extending from surface 122. The conveyance
may comprise an inner core of seven electrical conductors covered
by an insulating wrap. An inner and outer steel armor sheath may be
wrapped in a helix in opposite directions around the conductors.
The electrical conductors may be used for communicating power and
telemetry to surface 122. Information from fiber optic cable 106
may be gathered and/or processed by information handling system
120, discussed below. For example, signals recorded by fiber optic
cable 106 may be stored on memory and then processed by information
handling system 120. The processing may be performed real-time
during data acquisition or after recovery of fiber optic cable 106.
Processing may alternatively occur downhole or may occur both
downhole and at surface. In some embodiments, signals recorded by
fiber optic cable 106 may be conducted to information handling
system 120 by way of the conveyance. Information handling system
120 may process the signals, and the information contained therein
may be displayed for an operator to observe and stored for future
processing and reference. Without limitation, fiber optic cable 106
may be attached to coil tubing and/or the conveyance by any
suitable means. Coil tubing and the conveyance may be disposed
within production tubing 108 and/or wellbore 102 by any suitable
means.
[0014] FIGS. 6A-6D illustrates different examples of deployment of
fiber optic cable 106 in wellbore 102. As illustrated in FIG. 6A,
wellbore 102 deployed subterranean formation 118 may include
surface casing 600 in which production casing 602 may be deployed.
Additionally, production tubing 604 may be deployed within
production casing 602. In this example, fiber optic cable 106 may
be temporarily deployed in a wireline system in which a bottom hole
gauge 608 is connected to the distal end of fiber optic cable 106.
Further illustrated, fiber optic cable 106 may be coupled to a
fiber connection 606. Fiber connection 606 may operate with an
optical feedthrough system (itself comprising a series of wet- and
dry-mate optical connectors) in the wellhead that may optically
couple fiber optic cable 106 from the tubing hanger to the wellhead
instrument panel.
[0015] FIG. 6B illustrates a permeant deployment of fiber optic
cable 106. As illustrated in wellbore 102 deployed in subterranean
formation 118 may include surface casing 600 in which production
casing 602 may be deployed. Additionally, production tubing 604 may
be deployed within production casing 602. In examples, fiber optic
cable 106 is attached to the outside of production tubing 604 by
one or more cross-coupling protectors 610. Without limitation,
cross-coupling protectors 610 may be evenly spaced and may be
disposed on every other joint of production tubing 604. Further
illustrated, fiber optic cable 106 may be coupled to fiber
connection 606 at one end and bottom hole gauge 608 at the opposite
end.
[0016] FIG. 6C illustrates a permeant deployment of fiber optic
cable 106. As illustrated in wellbore 102 deployed in subterranean
formation 118 may include surface casing 600 in which production
casing 602 may be deployed. Additionally, production tubing 604 may
be deployed within production casing 602. In examples, fiber optic
cable 106 is attached to the outside of production casing 602 by
one or more cross-coupling protectors 610. Without limitation,
cross-coupling protectors 610 may be evenly spaced and may be
disposed on every other joint of production tubing 604. Further
illustrated, fiber optic cable 106 may be coupled to fiber
connection 606 at one end and bottom hole gauge 108 at the opposite
end.
[0017] FIG. 6D illustrates a coiled tubing operation in which fiber
optic cable 106 may be deployed temporarily. As illustrated in FIG.
6D, wellbore 102 deployed in subterranean formation 118 may include
surface casing 200 in which production casing 602 may be deployed.
Additionally, coiled tubing 612 may be deployed within production
casing 602. In this example, fiber optic cable 106 may be
temporarily deployed in a coiled tubing system in which a bottom
hole gauge 608 is connected to the distal end of downhole fiber.
Further illustrated, fiber optic cable 106 may be attached to
coiled tubing 612, which may move fiber optic cable 106 through
production casing 602. Further illustrated, fiber optic cable 106
may be coupled to fiber connection 606 at one end and bottom hole
gauge 608 at the opposite end. During operations, fiber optic cable
106 may be used to take measurements within wellbore 102, which may
be transmitted to the surface for further processing.
[0018] Referring back to FIG. 1, DAS system 104 may function and
operate to measure seismic waves 114 and/or reflected seismic waves
116. Seismic waves 116 may illuminate elements (not illustrated) in
formation 118. Seismic waves 114 and/or reflected seismic waves 116
may induce a dynamic strain signal in fiber optic cable 106, which
may be recorded by the DAS system on information handling system
120. Measuring dynamic strain in fiber optic cable 106 may include
a strain measurement, fiber curvature measurement, fiber
temperature measurement, and/or energy of backscattered light
measurement. A strain measurement may be performed by an operation
of Brillouin scattering (via Brillouin Optical Time-Domain
Reflectometry, BOTDR, or Brillouin Optical Time-Domain Analysis,
BOTDA), or Rayleigh scattering utilizing Optical Frequency Domain
Reflectometry (OFDR). A Fiber curvature measurement may be
performed using Polarization Optical Time Domain Reflectometry
(P-OTDR) or Polarization-Optical Frequency Domain Reflectometry
(P-OFDR). A Fiber temperature measurement may be performed
utilizing Raman DTS. An energy of backscattered light of DAS
measurement may be performed utilizing an automatic thresholding
scheme, the fiber end is set to the DAS channel for which the
backscattered light energy flat lines. The purpose of all these
measurements may be to compute the structure and properties of
formation 118 at different times. This may allow an operator to
perform reservoir monitoring.
[0019] Information handling system 120 may include any
instrumentality or aggregate of instrumentalities operable to
compute, estimate, classify, process, transmit, receive, retrieve,
originate, switch, store, display, manifest, detect, record,
reproduce, handle, or utilize any form of information,
intelligence, or data for business, scientific, control, or other
purposes. For example, an information handling system 120 may be a
personal computer, a network storage device, or any other suitable
device and may vary in size, shape, performance, functionality, and
price. Information handling system 120 may include random access
memory (RAM), one or more processing resources such as a central
processing unit 124 (CPU) or hardware or software control logic,
ROM, and/or other types of nonvolatile memory. Additional
components of the information handling system 120 may include one
or more disk drives 126, output devices 128, such as a video
display, and one or more network ports for communication with
external devices as well as an input device 130 (e.g., keyboard,
mouse, etc.). Information handling system 120 may also include one
or more buses operable to transmit communications between the
various hardware components.
[0020] Alternatively, systems and methods of the present disclosure
may be implemented, at least in part, with non-transitory
computer-readable media. Non-transitory computer-readable media may
include any instrumentality or aggregation of instrumentalities
that may retain data and/or instructions for a period of time.
Non-transitory computer-readable media may include, for example,
storage media such as a direct access storage device (e.g., a hard
disk drive or floppy disk drive), a sequential access storage
device (e.g., a tape disk drive), compact disk, CD-ROM, DVD, RAM,
ROM, electrically erasable programmable read-only memory (EEPROM),
and/or flash memory; as well as communications media such wires,
optical fibers, microwaves, radio waves, and other electromagnetic
and/or optical carriers; and/or any combination of the
foregoing.
[0021] Information handling system 120 may be connected to DAS
system which may further include a single mode-multimode ("SM-MM")
converter 132 and a Fiber Vertical Seismic Profile ("VSP")
interrogator 134. SM-MM converter 132 may be used to convert
between a single mode and a multimode for fiber communication.
Fiber VSP interrogator 134 may be used to emit light pulses into
the fiber optic cable 106 and translate the backscattered light
pulses to digital information, which may be read by information
handling system 120. In examples, information handling system 120
may communicate with DAS system 104 and act as a data processing
system that analyzes measured and/or collected information. This
processing may occur at surface 122 in real-time. Alternatively,
the processing may occur at surface 122 and/or at another
location.
[0022] It should be noted that information handling system 120 may
be connected to DAS system 104. Without limitation, information
handling system 120 may be a hard connection or a wireless
connection 138. Information handling system 120 may record and/or
process measurements from DAS system 104 individually and/or at the
same time.
[0023] Seismic system 136 may include a seismic source 142. As
illustrated, a vehicle 140 may house the seismic source 142.
Seismic source 142 may be used to propagate seismic waves into
subterranean formations 118. Without limitations, seismic source
142 may be a compressional source or a shear source. In examples,
seismic source 142 may a truck-mounted seismic vibrator. However,
without limitation, seismic source 142 may also include an air gun,
an explosive device, a vibroseis, and/or the like. Seismic source
142 may include a baseplate 144 that may be lowered so as to be in
contact with the ground. Vibrations of controlled and varying
frequency may be imparted to the ground through baseplate 144. When
the survey is completed, baseplate 144 may be raised, which may
allow so seismic source 142 and vehicle 140 to move to another
location.
[0024] During measurement operations, information handling system
120 may take into account reflected seismic waves 116 to produce a
VSP. In one example, the seismic refraction data may be processed
into a near-surface velocity model. Information handling system 120
may update the near-surface velocity model for seismic tomographic
reconstruction (i.e., either travel time or waveform data).
Further, information handling system 120 may update the travel time
used for travel time tomographic reconstruction of the near-surface
velocity model. This information may be used for reservoir
monitoring over any length of time.
[0025] As discussed above, DAS technology may suffer from a
fundamental problem arising out of positional uncertainty of DAS
channels. DAS channels are defined as regularly spaced physical
locations along the length of a fiber optic cable (e.g., DAS fiber)
at which seismic measurements are made. The distance between each
DAS channel is governed by the sampling rate of the optical
receiver that is used to convert the analogue backscattered light
signal into an electrical, digital data stream. The assumed
position of each DAS channel is based on the arrival time of the
backscattered light which in turn assumes a certain propagation
velocity of the emitted light pulse in fiber optic cable 106.
However, small deviations of the assumed propagation velocity, e.g.
due to temperature fluctuations in the wellbore as well as other
environmental effects may lead to subtle DAS channel spacing
mismatches which accumulate over depth. Moreover, the nominal
length of the surface fiber cable--defined as the length of fiber
optic cable 106 between the Fiber VSP interrogator 134 and the
wellhead fiber outlet--is usually not known precisely, causing a
static depth offset between the assumed and true location of the
recorded DAS channels. Additionally, fiber overstuffing which is
done to prevent damage to fiber optic cable 106 during deployment
in the well may further increase the overall positional uncertainty
of the recorded DAS data. In order to mitigate the positional
uncertainty of DAS channels, a methodology is discussed below to
invert picked travel times of the direct wave recorded on a DAS VSP
data set to simultaneously obtain the DAS channel locations and
anisotropic velocities of a 3D layered model. It should be noted
that the direct waves are compressional P waves that reach the DAS
fiber and are recorded at a DAS channel from the source without
reflecting off any seismic reflector. The DAS channel location
inversion may be constrained by a measured well trajectory (e.g.,
from a well deviation survey) and may potentially reduce
uncertainties from the range of tens of meters to a few meters
around a true location.
[0026] Without limitation, inversions may take into account travel
times. There are many well-known methods for picking the travel
times (first breaks) of the direct wave. A first breaks refer to
the arrival of the first P wave energy arrival at the DAS channels.
For example, a threshold detection method may be used or
alternatively a method of cross correlating a window around the
first break on a trace by trace basis may be used. For the forward
modeled travel time computation, one approach may be to use ray
tracing to compute arrival times, while an alternative approach may
be to use a travel time eikonal solver. An eikonal solver computes
travel times from a source to all points in a gridded velocity
model of the subsurface. The grid defines the distribution of
seismic properties of the earth subsurface. The subsurface velocity
model may be described by a constant isotropic medium, a constant
anisotropic medium, a layer based medium with isotropic or
anisotropic properties, or finally by a set of gridded cells with
isotropic or anisotropic properties. The inversion algorithm may be
performed by any one of a number of non-linear inversion schemes.
Non-linear inversion scheme may include evolutionary algorithms,
non-linear conjugate gradient methods, and a differential
evolution.
[0027] As discussed below, systems and methods may compute travel
times using shooting based ray tracing through a provided 3D
isotropic or anisotropic starting model. Additionally, the
anisotropy may be restricted to be up to a transversely isotropic
media with a vertical axis of symmetry (VTI). However, any order of
anisotropy may be included in the algorithm but increasing the
level of anisotropy may include additional source effort to build
enough ray travel path coverage of the subsurface model in order to
create a constrained solution. A ray tracer utilized in a
differential evolution algorithm may use a model that may stack
layers. The interface between each layer may be described by a
digitized 3D surface. For example, these interfaces may be created
from interpreted and digitized images provided by surface seismic
depth migration as a seismic depth image. As disclosed, additional
sources and DAS channels may be placed anywhere within the
subsurface media. This may enable the methodology to operate and/or
function in both vertical and deviated wells.
[0028] FIG. 2 illustrates an example of a 3D layered model 200. As
shown, rays 202 may be traced from three sources 204 (e.g., such as
a seismic source) to four DAS channels (not illustrated) in a 3D
layered model 200. Layers 208 are assigned VTI properties in 3D
layered model 200. Rays are paths along which seismic energy
travels from a seismic source 142 like an airgun or vibroseis to
the DAS channels, which collect the seismic data.
[0029] A ray tracer may be incorporated into a global inversion
scheme identified as Differential Evolution (DE). Without
limitations, the inversion scheme may also be any suitable
nonlinear global inversion scheme, such as, a particle swarm
optimization, classical genetic algorithm, and/or the like. A ray
tracer computes the travel times from source to DAS channel, DE is
the inversion scheme that tries to match the travel time data
collected from the seismic survey and hence improve the estimates
of the physical properties of the subsurface. DE is defined as a
population based evolutionary algorithm for optimizing a given
objective. As illustrated in the graph of FIG. 3, DE may minimize a
measure of misfit (L2 norm) between observed (measured) first
arrival travel times and travel times predicted by the ray tracer.
DE updates the VTI media (e.g., transversely isotropic media with
vertical axis of symmetry) parameters (Vp.sub.0, epsilon and delta)
along with location of DAS channels to find inversion results that
best fit the observed travel times.
[0030] In addition to the general principles, selected constraints
may be used to regularize the DE inversion. For example, search
limits may be selected for VTI media parameters for each layer 208
(e.g., referring to FIG. 2) being inverted for. Additionally,
search limits may be applied for the X, Y, and Z coordinates for
locations of DAS channels being inverted for simultaneously.
Without limitation, DE solutions may be penalized that have an
epsilon greater than delta and when the location of a DAS channel
is such that their distance from the well trajectory cross a
predefined threshold. This well trajectory is defined in terms of
point coordinates along the well. Application of constraints along
with the use of a global inversion may identify locations of DAS
channels that may be within a few meters from a true location as
evident from the graph of the synthetic test in FIG. 3. As noted
above, three sources 204 as identifying individual sources may be
limited due to data from the field. For example, limited data
reduces the number of sources and may cause estimation of VTI
parameters to suffer. However, the location of DAS channels were
constrained after a DE inversion. As noted above, the DE inversion
may be constrained to search windows that may be a few tens of
meters wide. Results from the DE inversion within those windows may
accurately locate the location of a DAS channel within a few
meters. It should be noted here that in a field dataset however,
the noise in the data and the inaccuracies of the picked horizons
may cause the locations of DAS channels to have larger inaccuracies
after inversion. Nonetheless, the error may be reduced
significantly compared to the erroneous estimates from DAS data
alone.
[0031] FIG. 4 is an example of workflow 400 for an overall
inversion algorithm for estimating layer properties and locations
of DAS channels (e.g., referring to FIG. 1) simultaneously from
first arrival travel times. Workflow 400 begins with block 402 for
generating an interface for a 3D layered model 200 (e.g., referring
to FIG. 2), for example, using a commercially available seismic
interpretation package and the data available. Without limitation,
3D layered model 200 may be any multi-dimensional layer model, for
example 2D, 3D, etc. In block 404, using the interface of the 3D
layered model 200, a time table and shot location table may be
prepared for a first arrival of a P-wave. From this information, in
block 406 the initial model layer properties (three P-wave
anisotropy parameters per layer) may be estimated and DAS channel
locations may also be estimated from available data. In blocked 408
the estimated properties and location may be used for preparing
overburden file of layer properties not being inverted for. In
block 410 a forward model may be prepared, and anisotropic ray
tracing may be run through the forward model to see if some
source-DAS channel combinations should be discarded and to store an
initial choice of ray parameters. After discarding combinations, in
block 412, the upper and lower limits for modeling parameters and
channel location search space may be defined for the forward model.
The channel location search space is defined as the area bound by
upper and lower limits in which a search is performed to identify a
channel location. In block 414 an inversion algorithm (differential
evolution) parameters like number of generations, crossover
probability and DE step size may be specified. After identifying an
inversion algorithm, in block 416 the chosen inversion may be
performed, and all population members are collected at the end of
the processing. Finally, in block 418 a best solution is picked
based on stored error predictions and calculating mean and standard
deviation of inverted model parameters to determine the location of
one or more distributed acoustic system channels. A more specific
workflow may be performed for a differential evolution.
[0032] FIG. 5 illustrates workflow 500 for a differential
evolution. Workflow 500 may begin with block 502 for defining one
or more search windows. In block 504, after defining a search
window a random population of solutions of any suitable size may be
generated. In block 506 the generated population may be evaluated
for each member by calculating error for each member. In block 508
one or more penalties may be added if solutions may not be smooth
enough, for example if the epsilon is less than delta, or distance
of DAS channels from well trajectory is not small enough. After
penalties, in block 510 a solution may be chosen that satisfies the
criteria in block 508, for example, where the epsilon is more than
delta or the distance of DAS channels may be similar to predicted
lengths. After choosing a solution, in block 512 a mutant solution
may be calculated. It should be noted that to calculate and
determine may be used interchangeably throughout this disclosure. A
mutant solution may be defined as adding a random number, a
mutation, chosen from a Gaussian distribution, or the like, to each
solution. The process may be repeated to generate a mutant
population of any size, wherein the amount of mutation in the
mutant population is proportional to the standard deviation of the
distribution, which may decrease with each new generation. After
populating a mutant population, in block 514 a crossover between
target solution from original population and corresponding mutant
solution to generate trial solutions may be applied. In block 516
trial solutions may be compared against target solutions and create
child population using a greedy criterion. Greedy criterion is
defined as an algorithm in an algorithmic strategy that makes the
best optimal choice at each small stage to lead to a globally
optimum solution. In block 518 child solutions are stored in
information handling system 120 as well as the corresponding error
values for each child solution. In block 520 it is determined if
stopping criteria has been satisfied. The stopping criteria
compares the child solutions to stored error predictions.
Additionally, the stopping criteria calculates a mean and standard
deviation of inverted model parameters from the search windows
established in block 502.
[0033] The preceding description provides various examples of the
systems and methods of use for identifying the location of one or
more distributed acoustic channels in a multi-dimensional model
interface. Disclosed below are various method steps and alternative
combinations of components.
[0034] Statement 1. A method may comprise generating a
multi-dimensional model interface with an information handling
system, preparing a time table for a first arrival of a P-wave
based at least in part on the multi-dimensional model interface,
estimating one or more initial model layer properties based at
least in part on the multi-dimensional model interface, estimating
a location of one or more distributed acoustic system channels
based at least in part on the multi-dimensional model interface,
creating a forward model based at least in part on the location of
the one or more distributed acoustic system channels and the one or
more initial model layer properties, running an anisotropic ray
tracing on the forward model, defining an upper limit and a lower
limit for model parameters within the forward model, specifying
parameters for an inversion for the model parameters, running the
inversion with the model parameters to populate one or more
members, selecting a solution from the one or more members based at
least in part on stored error predictions, and calculating a mean
and a standard deviation of an inverted model parameter to
determine the location of the one or more distributed acoustic
system channels.
[0035] Statement 2. The method of statement 1, wherein the
multi-dimensional model interface is a gridded velocity model.
[0036] Statement 3. The method of statements 1 or 2, further
comprising storing an initial choice of a ray parameter.
[0037] Statement 4. The method of statements 1-3, further
comprising defining the upper limit and the lower limit for a
channel location search space.
[0038] Statement 5. The method of statements 1-4, wherein the
inversion is a non-linear inversion.
[0039] Statement 6. The method of statement 5, wherein the
parameters for the inversion are a number of generations, a
crossover probability or a step size.
[0040] Statement 7. The method of statements 1-5, further
comprising collecting all population members from the
inversion.
[0041] Statement 8. The method of statements 1-5 or 7, wherein the
generating the multi-dimensional model interface is performed at
least in part with a seismic depth image.
[0042] Statement 9. The method of statements 1-5, 7, or 8, wherein
the multi-dimensional model interface includes at least three
P-wave anisotropy parameters per layer.
[0043] Statement 10. The method of statements 1-5, or 7-9, further
comprising disposing the one or more distributed acoustic system
channels into a wellbore.
[0044] Statement 11. A system may comprise a distributed acoustic
system, wherein the distributed acoustic system may comprise a
fiber optic cable and a seismic source. The system may further
comprise an information handling system configured to generate a
three dimensional model interface, prepare a time table for a first
arrival of a P-wave based at least in part on a multi-dimensional
model interface, estimate one or more initial model layer
properties based at least in part on the multi-dimensional model
interface, estimate a location of one or more distributed acoustic
system channels based at least in part on the multi-dimensional
model interface, create a forward model based at least in part on
the location of the one or more distributed acoustic system
channels and the one or more initial model layer properties, run an
anisotropic ray tracing on the forward model, define an upper limit
and a lower limit for model parameters within the forward model,
specify parameters for an inversion for the model parameter, run
the inversion with the model parameters to populate one or more
members, elect a solution from the one or more members based at
least in part on stored error predictions, and calculate a mean and
a standard deviation of an inverted model parameter to determine
the location of the one or more distributed acoustic system
channels.
[0045] Statement 12. The system of statement 11, wherein the
multi-dimensional model interface is a gridded velocity model.
[0046] Statement 13. The system of statements 11 or 12, wherein the
information handling system is configured to store an initial
choice of a ray parameter.
[0047] Statement 14. The system of statements 11-13, wherein the
information handling system is configured to define the upper limit
and the lower limit for a channel location search space.
[0048] Statement 15. The system of statements 11-14, wherein the
inversion is a non-linear inversion.
[0049] Statement 16. The system of statements 11-15, wherein the
parameters for the inversion are a number of generations, a
crossover probability, or a step size.
[0050] Statement 17. A method may comprise defining a search window
for a multi-dimensional model interface to locate one or more
distributed acoustic system channels, generating a random
population of solutions for a location of the one or more
distributed acoustic system channels, determining an error for at
least one member of the population of solutions, adding at least
one penalty to the population of solutions, choosing a solution
from the population of solutions, determining a mutant solution for
the population of solutions, generating a trial solution based at
least in part on the mutant solution and the population of
solutions, comparing the trial solution to a target solution to
create one or more child solutions, and storing the one or more
child solutions within an information handling system.
[0051] Statement 18. The method of statement 17, wherein the one or
more child solutions are found from a greedy criterion.
[0052] Statement 19. The method of statements 17 or 18, further
comprising applying a stopping criterion to the one or more child
solutions.
[0053] Statement 20. The method of statement 19, wherein the
stopping criterion compare the one or more child solutions to error
predictions.
[0054] It should be understood that, although individual examples
may be discussed herein, the present disclosure covers all
combinations of the disclosed examples, including, without
limitation, the different component combinations, method step
combinations, and properties of the system. It should be understood
that the compositions and methods are described in terms of
"comprising," "containing," or "including" various components or
steps, the compositions and methods can also "consist essentially
of" or "consist of" the various components and steps. Moreover, the
indefinite articles "a" or "an," as used in the claims, are defined
herein to mean one or more than one of the element that it
introduces.
[0055] For the sake of brevity, only certain ranges are explicitly
disclosed herein. However, ranges from any lower limit may be
combined with any upper limit to recite a range not explicitly
recited, as well as, ranges from any lower limit may be combined
with any other lower limit to recite a range not explicitly
recited, in the same way, ranges from any upper limit may be
combined with any other upper limit to recite a range not
explicitly recited. Additionally, whenever a numerical range with a
lower limit and an upper limit is disclosed, any number and any
included range falling within the range are specifically disclosed.
In particular, every range of values (of the form, "from about a to
about b," or, equivalently, "from approximately a to b," or,
equivalently, "from approximately a-b") disclosed herein is to be
understood to set forth every number and range encompassed within
the broader range of values even if not explicitly recited. Thus,
every point or individual value may serve as its own lower or upper
limit combined with any other point or individual value or any
other lower or upper limit, to recite a range not explicitly
recited.
[0056] Therefore, the present examples are well adapted to attain
the ends and advantages mentioned as well as those that are
inherent therein. The particular examples disclosed above are
illustrative only, and may be modified and practiced in different
but equivalent manners apparent to those skilled in the art having
the benefit of the teachings herein. Although individual examples
are discussed, the disclosure covers all combinations of all of the
examples. Furthermore, no limitations are intended to the details
of construction or design herein shown, other than as described in
the claims below. Also, the terms in the claims have their plain,
ordinary meaning unless otherwise explicitly and clearly defined by
the patentee. It is therefore evident that the particular
illustrative examples disclosed above may be altered or modified
and all such variations are considered within the scope and spirit
of those examples. If there is any conflict in the usages of a word
or term in this specification and one or more patent(s) or other
documents that may be incorporated herein by reference, the
definitions that are consistent with this specification should be
adopted.
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